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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/87024


    Title: 應用機器學習於SiC表面雷射加工之研究
    Authors: 陳冠廷;Chen, Kuan-Ting
    Contributors: 機械工程學系
    Keywords: SiC;飛秒雷射;機器學習;SiC;femtosecond laser;machine learning
    Date: 2021-10-13
    Issue Date: 2021-12-07 13:46:12 (UTC+8)
    Publisher: 國立中央大學
    Abstract: SiC 為第三代半導體的重要原料,因具有寬能隙、耐高溫、耐
    高壓與低耗損等特性,是目前產業界主要的發展方向之一。SiC 的
    硬度極高,亦造成生產時間及成本的耗費。化學機械研磨為目前半
    導體晶圓主要的拋光技術,為有效提升 SiC 晶圓拋光製程之材料移
    除率,利用飛秒雷射輔助加工技術進行 SiC 晶圓表面改質及材料移
    除,使其有效縮短後續化學機械研磨加工時間,提升產能,增加 SiC
    的工業應用。本論文以上述為出發點,目標在建立一 SiC 雷射表面
    加工品質預測模型,收集 SiC 雷射表面加工之雷射相關參數與加工
    品質,以常見的機器學習演算法如決策樹、隨機森林、Extra Trees、
    Gradient Boosting 及 Stacking 建立模型,了解各雷射加工參數與加
    工品質之間的關係,穩定加工品質,作為日後與 SiC 相關雷射加工
    之研究準備。;SiC is an important raw material for third-generation
    semiconductors. Because of its wide energy gap, high temperature
    resistance, high pressure resistance, and low loss, it is one of the main
    development directions of the current industry. The hardness of SiC is
    extremely high, which also causes the consumption of production time
    and cost. Chemical mechanical polishing is currently the main polishing
    technology for semiconductor wafers. In order to effectively improve
    the material removal rate of the SiC wafer polishing process,
    femtosecond laser assisted processing technology is used to modify the
    surface of SiC wafers and remove materials to make it effective Shorten
    the follow-up chemical mechanical grinding processing time, increase
    production capacity, and increase the industrial application of SiC. This
    paper takes the above as the starting point and aims to establish a SiC
    laser surface processing quality prediction model. Collect laser-related
    parameters and processing quality of SiC laser surface processing, and
    build models with common machine learning algorithms such as
    decision trees, random forests, Extra Trees, Gradient Boosting and
    Stacking, Understand the relationship between laser processing
    parameters and processing quality, stabilize processing quality, and
    prepare for future research related to SiC laser processing.
    Appears in Collections:[Graduate Institute of Mechanical Engineering] Electronic Thesis & Dissertation

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